Patients in these two clusters had severe insulin-deficient diabetes, characterized by low age at onset, relatively low BMI, low insulin secretion, and poor metabolic control; or severe insulin-resistant diabetes, characterized by insulin resistance and high BMI. These groups contained a respective 17.5% and 15.3% of all study patients (8980, identified in the Swedish All New Diabetics in Scania registry).

The insulin-resistant group had a particularly high risk for developing kidney disease as their diabetes progressed, with the risk increase for end-stage kidney disease approaching fivefold higher than that of patients in the lowest-risk cluster. The researchers note that this high risk was in spite of “reasonably low” HbA1c levels of around 50 mmol/mol, “suggesting that glucose-lowering therapy is not the optimum way of preventing this complication.”

The insulin-deficient group had the highest risk for developing retinopathy, although the risk differences between the groups were not as marked for this outcome.

They also suggest that randomized trials could target insulin secretion and resistance specifically in these groups of patients.

The other three clusters comprised GADA-positive patients with early-onset disease, relatively low BMI, poor metabolic control, and insulin deficiency (6.4% of patients); and two groups of fairly low-risk patients – one with high BMI but no insulin resistance (21.6%) and one with older age at onset than the other groups and “modest” metabolic impairments (39.1%).

Rerunning the analysis using a further three independent cohorts with nearly 6000 patients in total produced similar results.

The researchers believe that the identified clusters represent partly distinct underlying disease mechanisms, rather than different disease stages, because the same clusters emerged regardless of whether patients were newly diagnosed or had a long disease duration. However, they note that it remains to be determined whether patients may move between clusters over time.

They caution: “We cannot at this stage claim that the new clusters represent different aetiologies of diabetes, nor that this clustering is the optimal classification of diabetes subtypes.”

In a linked commentary, Rob Sladek (McGill University, Montréal, Québec, Canada) also stresses that the study involved only Scandinavian patients, so the results may not apply to other racial groups.

“Nevertheless, the finding that simple parameters assessed at the time of diagnosis could reliably stratify patients with diabetes according to prognosis is compelling and poses the challenge of development of methods to predict outcomes of patients with type 2 diabetes that are more generalisable and comprehensive,” he concludes.